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license: apache-2.0
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---
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license: apache-2.0
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---
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# MVInpainter
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[NeurIPS 2024] MVInpainter: Learning Multi-View Consistent Inpainting to Bridge 2D and 3D Editing
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[[arXiv]](https://arxiv.org/pdf/2408.08000) [[Project Page]](https://ewrfcas.github.io/MVInpainter/)
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Codes and models will be open-released soon!
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Codes organization is working in progress.
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### Dataset preparation (training)
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1. Downloading [Co3dv2](https://github.com/facebookresearch/co3d), [MVImgNet](https://github.com/GAP-LAB-CUHK-SZ/MVImgNet) for MVInpainter-O.
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Downloading [Real10k](https://google.github.io/realestate10k/download.html), [DL3DV](https://github.com/DL3DV-10K/Dataset), [Scannet++](https://kaldir.vc.in.tum.de/scannetpp) for MVInpainter-F.
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2. Downloading information of indices and masking formats from [Link](), and put them to ```./data```. Note that we remove some dirty samples from aforementioned datasets. We additionally provide complete foreground masks for MVImgNet through ```CarveKit```.
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### Pretrained weights (training)
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Put these weights to ```./check_points```
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1. [SD1.5-inpainting]()
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2. [AnimateDiff weights](). We revise the key name for easier ```peft``` usages.
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## Cite
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If you found our program helpful, please consider citing:
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```
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@article{cao2024mvinpainter,
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title={MVInpainter: Learning Multi-View Consistent Inpainting to Bridge 2D and 3D Editing},
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author={Cao, Chenjie and Yu, Chaohui and Fu, Yanwei and Wang, Fan and Xue, Xiangyang},
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journal={arXiv preprint arXiv:2408.08000},
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year={2024}
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}
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```
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